Abstract
We get sharp estimates for the distribution function of nonnegative weights, which satisfy so called condition. For particular choices of parameters , this condition becomes an -condition or Reverse Hölder condition. We also get maximizers for these sharp estimates. We use the Bellman technique and try to carefully present and motivate our tactics. As an illustration of how these results can be used, we deduce the following result: if a weight is in then it self-improves to a weight, which satisfies a Reverse Hölder condition.
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